AI-ACCELERATED DRUG DISCOVERY

Focused On-demand Library for Laminin subunit beta-1

Available from Reaxense
Predicted by Alphafold

Focused On-demand Libraries - Reaxense Collaboration

Explore the Potential with AI-Driven Innovation

The specialised, focused library is developed on demand with the most recent virtual screening and parameter assessment technology, guided by the Receptor.AI drug discovery platform. This approach exceeds the capabilities of traditional methods and offers compounds with higher activity, selectivity, and safety.

The compounds are cherry-picked from the vast virtual chemical space of over 60B molecules. The synthesis and delivery of compounds is facilitated by our partner Reaxense.

In the library, a selection of top modulators is provided, each marked with 38 ADME-Tox and 32 parameters related to physicochemical properties and drug-likeness. Also, every compound comes with its best docking poses, affinity scores, and activity scores, providing a comprehensive overview.

Our top-notch dedicated system is used to design specialised libraries.

 Fig. 1. The sreening workflow of Receptor.AI

Our methodology employs molecular simulations to explore a wide array of proteins, capturing their dynamic states both individually and within complexes. Through ensemble virtual screening, we address conformational mobility, uncovering binding sites within functional regions and remote allosteric locations. This thorough exploration ensures no potential mechanism of action is overlooked, aiming to discover novel therapeutic targets and lead compounds across an extensive spectrum of biological functions.

Key features that set our library apart include:

  • The Receptor.AI platform integrates extensive information about the target protein, such as historical experiments, academic research, known ligands, and structural insights, thereby increasing the likelihood of identifying highly relevant compounds.
  • The platform’s sophisticated molecular simulations are designed to discover potential binding sites, ensuring that our focused library is optimal for the discovery of allosteric inhibitors and binders for cryptic pockets.
  • With over 50 customisable AI models, verified through extensive testing in commercial drug discovery and research, Receptor.AI is efficient, reliable, and precise. These models are essential in the production of our focused libraries.
  • Receptor.AI not only produces focused libraries but also provides full services and solutions at every stage of preclinical drug discovery, with a success-based pricing structure that aligns our interests with the success of your project.

partner

Reaxense

upacc

P07942

UPID:

LAMB1_HUMAN

Alternative names:

Laminin B1 chain; Laminin-1 subunit beta; Laminin-10 subunit beta; Laminin-12 subunit beta; Laminin-2 subunit beta; Laminin-6 subunit beta; Laminin-8 subunit beta

Alternative UPACC:

P07942; Q14D91

Background:

Laminin subunit beta-1, known by alternative names such as Laminin B1 chain and Laminin-2 subunit beta, plays a pivotal role in the embryonic development by mediating cell attachment, migration, and organization into tissues. It is crucial for the cerebral cortex's laminar architecture and the integrity of the basement membrane, serving as an anchor for radial glial cells and a barrier to migrating neurons.

Therapeutic significance:

Laminin subunit beta-1's involvement in Lissencephaly 5, a severe brain malformation, underscores its therapeutic significance. Understanding its role could lead to novel strategies for treating this and potentially other neurodevelopmental disorders.

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